Over the course of the past decade there has emerged a growing demand for risk transparency by the clients of investment firms as well as the regulators of those firms. This demand has been spurred by repeated crises in financial markets that have led to substantial losses. The most cited examples among hedge funds and other investment firms are the collapse of Long Term Capital Management (LTCM) in 1998, where clients lost well in excess of a billion dollars, and of Granite Partners in 1994, where clients lost over half a billion dollars. In both cases, the repercussions of the collapse were felt throughout the banking and investment banking community. Secondary losses due to the reduction in market liquidity and the loss in confidence in the fund's creditors were many times the losses of the investment firms responsible for the crises. Because of these secondary effects, as well as several well-publicized failures among investment banks and commercial banks, such as the mortgage and Treasury losses that led to the demise of Kidder Peabody in 1994, the same demand for risk transparency has been voiced toward the investment banks and commercial banks.
A number of regulatory authorities, including the Bank of International Settlement and the Federal Reserve, have demanded increasingly detailed risk reporting among the financial institutions that they regulate. Similar demands have come from quasi-regulatory bodies and professional groups in the investment and hedge fund community, as illustrated by the President's Report that followed the LTCM collapse, and the Investor Risk Committee of the International Association of Financial Engineers. Clients who invest in investment firms and hedge funds, the consultants who represent them and so-called “fund of funds” that invest on their behalf also have clamored for improved risk reporting in order to better gauge the potential for future crises.
There is broad agreement on the measures that are required for adequate risk management and reporting. These include measures, collectively known as “value at risk” of “VaR” measures, that provide an estimate of the probability of loss. These range from simple standard deviation estimates of portfolio returns to the construction of sophisticated, specialized return distributions that attempt to take into account the potential for jumps and related “fat tail” properties of security returns. Other analyses include stress tests that run the investment firm's portfolio through historical or prospective disaster scenarios. For example, the positions might be stressed by seeing the losses the positions would have experienced over the course of the 1987 market crash or the 1997 Asia crisis. Other risk analysis breaks portfolio positions into key risk factors, such as interest rate risk, oil-related risk, and credit risk. Yet other risk analysis uses a statistical analysis of position information to determine trading style factors, such as a tendency to follow trends or to focus on value-oriented stocks.
There are related measures that deal with performance. These measures usually combine risk measures with some measure of portfolio returns. For example, the Sharpe Ratio and the Information Ratio both measure performance by looking at the ratio of return to the standard deviation of return. For the purposes of the description and embodiments, my discussion of risk measures and risk analysis relates to both risk and performance. The inventor envisions application to any algorithm that employs position information, especially algorithms that have the property of homogeneity which will be discussed below.
There is also broad agreement that for the risk analysis to be of value for due diligence or fiduciary purposes, it should be run independent of the Investment Firm. That is, ideally the client or regulator would rather have their own agent or trusted third party do the risk analysis than rely on analysis provided by the Investment Firm itself.
These risk measures require the underlying positions of the Investment Firm as input. Each position will be affected differently by changes in market factors and will have a distinct reaction to economic events. And obviously a larger exposure or holding will lead to greater risk. Unfortunately, the need to use the underlying security positions to do risk computations creates conflicts between the demand for independent risk analysis and the demands that investment firms have for position confidentiality.
Position transparency raises a number of risks for the Investment Firm. One risk is that others will piggyback on their positions, both profiting from their analysis and diluting their trading opportunities. Another is that the methodology they employ for trading might be revealed by an analysis of their positions. And, most critically, knowledge of their positions might lead others to trade against them. This can be particularly costly when an Investment Firm has a large position, especially a large short position, where predatory activity in the market can create a short squeeze forcing the Investment Firm out of what might otherwise be a profitable position.
There is thus an increasing demand for a method to provide the position information in a way that allows the computation of risk information while keeping that position information confidential.